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https://github.com/wassname/catalyst.git
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205 lines
6.0 KiB
Python
205 lines
6.0 KiB
Python
#
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# Copyright 2015 Quantopian, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import division
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import abc
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import math
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from six import with_metaclass
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from zipline.finance.transaction import create_transaction
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SELL = 1 << 0
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BUY = 1 << 1
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STOP = 1 << 2
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LIMIT = 1 << 3
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class LiquidityExceeded(Exception):
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pass
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DEFAULT_VOLUME_SLIPPAGE_BAR_LIMIT = 0.025
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class SlippageModel(with_metaclass(abc.ABCMeta)):
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"""Abstract interface for defining a slippage model.
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"""
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def __init__(self):
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self._volume_for_bar = 0
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@property
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def volume_for_bar(self):
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return self._volume_for_bar
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@abc.abstractproperty
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def process_order(self, data, order):
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"""Process how orders get filled.
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Parameters
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----------
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data : BarData
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The data for the given bar.
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order : Order
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The order to simulate.
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Returns
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-------
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execution_price : float
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The price to execute the trade at.
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execution_volume : int
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The number of shares that could be filled. This may not be all
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the shares ordered in which case the order will be filled over
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multiple bars.
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"""
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pass
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def simulate(self, data, asset, orders_for_asset):
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self._volume_for_bar = 0
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volume = data.current(asset, "volume")
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if volume == 0:
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return
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# can use the close price, since we verified there's volume in this
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# bar.
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price = data.current(asset, "close")
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dt = data.current_dt
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for order in orders_for_asset:
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if order.open_amount == 0:
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continue
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order.check_triggers(price, dt)
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if not order.triggered:
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continue
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txn = None
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try:
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execution_price, execution_volume = \
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self.process_order(data, order)
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if execution_price is not None:
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txn = create_transaction(
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order,
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data.current_dt,
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execution_price,
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execution_volume
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)
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except LiquidityExceeded:
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break
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if txn:
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self._volume_for_bar += abs(txn.amount)
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yield order, txn
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def __call__(self, bar_data, asset, current_orders):
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return self.simulate(bar_data, asset, current_orders)
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class VolumeShareSlippage(SlippageModel):
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"""Model slippage as a function of the volume of shares traded.
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"""
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def __init__(self, volume_limit=DEFAULT_VOLUME_SLIPPAGE_BAR_LIMIT,
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price_impact=0.1):
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self.volume_limit = volume_limit
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self.price_impact = price_impact
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super(VolumeShareSlippage, self).__init__()
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def __repr__(self):
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return """
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{class_name}(
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volume_limit={volume_limit},
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price_impact={price_impact})
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""".strip().format(class_name=self.__class__.__name__,
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volume_limit=self.volume_limit,
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price_impact=self.price_impact)
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def process_order(self, data, order):
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volume = data.current(order.asset, "volume")
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max_volume = self.volume_limit * volume
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# price impact accounts for the total volume of transactions
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# created against the current minute bar
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remaining_volume = max_volume - self.volume_for_bar
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if remaining_volume < 1:
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# we can't fill any more transactions
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raise LiquidityExceeded()
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# the current order amount will be the min of the
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# volume available in the bar or the open amount.
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cur_volume = int(min(remaining_volume, abs(order.open_amount)))
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if cur_volume < 1:
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return None, None
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# tally the current amount into our total amount ordered.
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# total amount will be used to calculate price impact
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total_volume = self.volume_for_bar + cur_volume
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volume_share = min(total_volume / volume,
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self.volume_limit)
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price = data.current(order.asset, "close")
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simulated_impact = volume_share ** 2 \
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* math.copysign(self.price_impact, order.direction) \
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* price
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impacted_price = price + simulated_impact
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if order.limit:
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# this is tricky! if an order with a limit price has reached
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# the limit price, we will try to fill the order. do not fill
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# these shares if the impacted price is worse than the limit
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# price. return early to avoid creating the transaction.
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# buy order is worse if the impacted price is greater than
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# the limit price. sell order is worse if the impacted price
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# is less than the limit price
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if (order.direction > 0 and impacted_price > order.limit) or \
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(order.direction < 0 and impacted_price < order.limit):
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return None, None
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return (
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impacted_price,
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math.copysign(cur_volume, order.direction)
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)
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class FixedSlippage(SlippageModel):
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"""Model slippage as a fixed spread.
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Parameters
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----------
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spread : float, optional
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spread / 2 will be added to buys and subtracted from sells.
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"""
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def __init__(self, spread=0.0):
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self.spread = spread
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def process_order(self, data, order):
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price = data.current(order.asset, "close")
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return (
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price + (self.spread / 2.0 * order.direction),
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order.amount
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)
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